Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinomaCitation formats

  • Authors:
  • The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium

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Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma. / The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium.

In: Nature Communications, Vol. 10, No. 1, 3101, 12.2019.

Research output: Contribution to journalArticle

Harvard

The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium 2019, 'Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma', Nature Communications, vol. 10, no. 1, 3101. https://doi.org/10.1038/s41467-019-10898-3

APA

The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium (2019). Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma. Nature Communications, 10(1), [3101]. https://doi.org/10.1038/s41467-019-10898-3

Vancouver

The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium. Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma. Nature Communications. 2019 Dec;10(1). 3101. https://doi.org/10.1038/s41467-019-10898-3

Author

The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium. / Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma. In: Nature Communications. 2019 ; Vol. 10, No. 1.

Bibtex

@article{aa35bb320e7b4a7e8661980e1123a38c,
title = "Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma",
abstract = "The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy.",
author = "{The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium} and Mourikis, {Thanos P.} and Lorena Benedetti and Elizabeth Foxall and Damjan Temelkovski and Joel Nulsen and Juliane Perner and Matteo Cereda and Jesper Lagergren and Michael Howell and Christopher Yau and Fitzgerald, {Rebecca C.} and Paola Scaffidi and Ayesha Noorani and Edwards, {Paul A.W.} and Elliott, {Rachael Fels} and Nicola Grehan and Barbara Nutzinger and Caitriona Hughes and Elwira Fidziukiewicz and Jan Bornschein and Shona MacRae and Jason Crawte and Alex Northrop and Gianmarco Contino and Xiaodun Li and {de la Rue}, Rachel and Annalise Katz-Summercorn and Sujath Abbas and Daniel Loureda and Maria O’Donovan and Ahmad Miremadi and Shalini Malhotra and Monika Tripathi and Simon Tavar{\'e} and Lynch, {Andy G.} and Matthew Eldridge and Maria Secrier and Lawrence Bower and Ginny Devonshire and Sriganesh Jammula and Jim Davies and Charles Crichton and Nick Carroll and Peter Safranek and Andrew Hindmarsh and Vijayendran Sujendran and Hayes, {Stephen J.} and Yeng Ang and Andrew Sharrocks and Walker, {Robert C.}",
year = "2019",
month = "12",
doi = "10.1038/s41467-019-10898-3",
language = "English",
volume = "10",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Springer Nature",
number = "1",

}

RIS

TY - JOUR

T1 - Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

AU - The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium

AU - Mourikis, Thanos P.

AU - Benedetti, Lorena

AU - Foxall, Elizabeth

AU - Temelkovski, Damjan

AU - Nulsen, Joel

AU - Perner, Juliane

AU - Cereda, Matteo

AU - Lagergren, Jesper

AU - Howell, Michael

AU - Yau, Christopher

AU - Fitzgerald, Rebecca C.

AU - Scaffidi, Paola

AU - Noorani, Ayesha

AU - Edwards, Paul A.W.

AU - Elliott, Rachael Fels

AU - Grehan, Nicola

AU - Nutzinger, Barbara

AU - Hughes, Caitriona

AU - Fidziukiewicz, Elwira

AU - Bornschein, Jan

AU - MacRae, Shona

AU - Crawte, Jason

AU - Northrop, Alex

AU - Contino, Gianmarco

AU - Li, Xiaodun

AU - de la Rue, Rachel

AU - Katz-Summercorn, Annalise

AU - Abbas, Sujath

AU - Loureda, Daniel

AU - O’Donovan, Maria

AU - Miremadi, Ahmad

AU - Malhotra, Shalini

AU - Tripathi, Monika

AU - Tavaré, Simon

AU - Lynch, Andy G.

AU - Eldridge, Matthew

AU - Secrier, Maria

AU - Bower, Lawrence

AU - Devonshire, Ginny

AU - Jammula, Sriganesh

AU - Davies, Jim

AU - Crichton, Charles

AU - Carroll, Nick

AU - Safranek, Peter

AU - Hindmarsh, Andrew

AU - Sujendran, Vijayendran

AU - Hayes, Stephen J.

AU - Ang, Yeng

AU - Sharrocks, Andrew

AU - Walker, Robert C.

PY - 2019/12

Y1 - 2019/12

N2 - The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy.

AB - The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy.

UR - http://www.scopus.com/inward/record.url?scp=85069459995&partnerID=8YFLogxK

U2 - 10.1038/s41467-019-10898-3

DO - 10.1038/s41467-019-10898-3

M3 - Article

C2 - 31308377

AN - SCOPUS:85069459995

VL - 10

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

IS - 1

M1 - 3101

ER -